kangar00
Kernel Approaches for Nonlinear Genetic Association Regression
Methods to extract information on pathways, genes and various single-nucleotid polymorphisms (SNPs) from online databases. It provides functions for data preparation and evaluation of genetic influence on a binary outcome using the logistic kernel machine test (LKMT). Three different kernel functions are offered to analyze genotype information in this variance component test: A linear kernel, a size-adjusted kernel and a network-based kernel).
- Version1.4.2
- R versionunknown
- LicenseGPL-2
- Needs compilation?No
- Last release05/09/2024
Documentation
Team
- Juliane ManitzMaintainerShow author details
- Benjamin HofnerShow author detailsRolesAuthor
- Stefanie FriedrichsShow author detailsRolesAuthor
- Patricia BurgerShow author detailsRolesAuthor
- Ngoc Thuy HaShow author detailsRolesAuthor
- Saskia FreytagShow author detailsRolesContributor
- Heike BickeboellerShow author detailsRolesContributor
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- Imports6 packages
- Suggests1 package
- Reverse Suggests1 package